The expressive declarative toolkit for composing predicates in TypeScript or JavaScript
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Mar 10, 2023 - TypeScript
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The expressive declarative toolkit for composing predicates in TypeScript or JavaScript
A design automation framework to engineer decision diagrams yourself
bdd eda add bmd formal-verification decision-diagrams hardware-testing boolean-function bhd pseudo-boolean kfdd phdd
A fast and certifying solver for quantified Boolean formulas.
Lightweight condition parsing and building of evaluation expressions
C++ header-only ESOP library
Local computation of immediate neighbours of a given monotone non-degenerate Boolean function
Python Tool for Model Revision of Boolean Networks
Minimal disjunctive normal form (MDNF): Table and Result in Qt
qt table boolean-algebra boolean-logic boolean-function logical-function minimal-disjunctive-normal-form mdnf
Learning A Boolean function with features and Data points
Python package to determine characteristics of Boolean functions [noise sensitivity, expected values, etc.]
Creating and analyzing interaction graphs based on boolean functions
python java graph graph-algorithms makefile bruteforce computation-graph research-project molecules cancer-research boolean-function cyclic-redundancy-check
Web app that helps you with subject "Digitalna logika" at FER. Check it out!
Discrete Mathematics course at ITMO University
automata probability discrete-mathematics combinatorics generating-function turing-machine compression-algorithm planar-graphs matroids boolean-function hamiltonian-cycles cf-grammar
[DEPRECATED] This repository is no longer maintained.
Generate a perfect disjunctive normal form (PDNF) and a perfect conjunctive normal form (PCNF) for boolean functions generator
Rust library to compute the algebraic immunity of Boolean function
Re-adapted implementation of Adversarial neural network model described in Learning to Protect Communications with Adversarial Neural Cryptography (Martín Abadi & David G. Andersen, 2016). The primary code is authored by Liam Schoneveld (https://nlml.github.io/neural-networks/adversarial-neural-cryptography/).
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